How do you check that someone did not e.g. bind something different to "len"?
On Wed, Nov 4, 2015 at 8:50 AM, Victor Stinner <victor.stin...@gmail.com> wrote: > Hi, > > I'm writing a new "FAT Python" project to try to implement optimizations in > CPython (inlining, constant folding, move invariants out of loops, etc.) > using a "static" optimizer (not a JIT). For the background, see the thread > on python-ideas: > https://mail.python.org/pipermail/python-ideas/2015-October/036908.html > > See also the documentation: > https://hg.python.org/sandbox/fatpython/file/tip/FATPYTHON.rst > https://hg.python.org/sandbox/fatpython/file/tip/ASTOPTIMIZER.rst > > I implemented the most basic optimization to test my code: replace calls to > builtin functions (with constant arguments) with the result. For example, > len("abc") is replaced with 3. I reached the second milestone: it's now > possible to run the full Python test suite with these optimizations enabled. > It confirms that the optimizations don't break the Python semantic. > > Example: > --- >>>> def func(): > ... return len("abc") > ... >>>> import dis >>>> dis.dis(func) > 2 0 LOAD_GLOBAL 0 (len) > 3 LOAD_CONST 1 ('abc') > 6 CALL_FUNCTION 1 (1 positional, 0 keyword pair) > 9 RETURN_VALUE > >>>> len(func.get_specialized()) > 1 >>>> specialized=func.get_specialized()[0] >>>> dis.dis(specialized['code']) > 2 0 LOAD_CONST 1 (3) > 3 RETURN_VALUE >>>> len(specialized['guards']) > 2 > >>>> func() > 3 > >>>> len=lambda obj: "mock" >>>> func() > 'mock' >>>> func.get_specialized() > [] > --- > > The function func() has specialized bytecode which returns directly 3 > instead of calling len("abc"). The specialized bytecode has two guards > dictionary keys: builtins.__dict__['len'] and globals()['len']. If one of > these keys is modified, the specialized bytecode is simply removed (when the > function is called) and the original bytecode is executed. > > > You cannot expect any speedup at this milestone, it's just to validate the > implementation. You can only get speedup if you implement *manually* > optimizations. See for example posixpath.isabs() which inlines manually the > call to the _get_sep() function. More optimizations will be implemented in > the third milestone. I don't know yet if I will be able to implement > constant folding, function inlining and/or moving invariants out of loops. > > > Download, compile and test FAT Python with: > > hg clone http://hg.python.org/sandbox/fatpython > ./configure && make && ./python -m test test_astoptimizer test_fat > > > Currently, only 24 functions are specialized in the standard library. > Calling a builtin function with constant arguments in not common (it was > expected, it's only the first step for my optimizer). But 161 functions are > specialized in tests. > > > To be honest, I had to modify some tests to make them pass in FAT mode. But > most changes are related to the .pyc filename, or to the exact size in bytes > of dictionary objects. > > FAT Python is still experimental. Currently, the main bug is that the AST > optimizer can optimize a call to a function which is not the expected > builtin function. I already started to implement code to understand > namespaces (detect global and local variables), but it's not enough yet to > detect when a builtin is overriden. See TODO.rst for known bugs and > limitations. > > Victor > > _______________________________________________ > Python-Dev mailing list > Python-Dev@python.org > https://mail.python.org/mailman/listinfo/python-dev > Unsubscribe: > https://mail.python.org/mailman/options/python-dev/fijall%40gmail.com > _______________________________________________ Python-Dev mailing list Python-Dev@python.org https://mail.python.org/mailman/listinfo/python-dev Unsubscribe: https://mail.python.org/mailman/options/python-dev/archive%40mail-archive.com
